Reporting your whole team actually trusts.
Live dashboards built on your modelled data, refreshed on a schedule, and delivered where your team already works. No one logs into anything new, and no one rebuilds a spreadsheet on Monday.
Executive Overview
Advertising
Products
AI Insights
| Channel | Spend | ROAS | CAC | Δ |
|---|---|---|---|---|
| Meta Ads | $42,180 | 3.9× | $36.40 | +18% |
| Google Ads | $31,060 | 4.6× | $29.80 | +6% |
| TikTok Ads | $8,420 | 1.2× | $71.20 | −34% |
| Amazon SP | $12,740 | 5.1× | $24.10 | +11% |
| SKU | Product | Revenue | Margin | % | Δ |
|---|---|---|---|---|---|
| #104 | Premium Hoodie | $61,240 | 42.3% | +18% | |
| #203 | Crewneck Sweatshirt | $48,910 | 38.7% | +12% | |
| #305 | Performance Tee | $39,480 | 34.1% | +5% | |
| #204 | Signature Cap | $27,360 | 28.9% | −3% | |
| #118 | Merino Beanie | $21,050 | 26.4% | +2% | |
| #412 | Trail Shorts | $18,720 | 19.8% | −9% |
Example output · illustrative data · runs in your own accounts
You'll get the most out of this if…
- Your team asks the same five questions every week and someone answers them by hand.
- You have dashboards, but nobody quite believes the numbers on them.
- Ad decisions are being made on platform-reported ROAS.
- You need one view that covers Shopify and Amazon together, not two separate ones.
Most dashboards report. Very few reconcile.
Platform-native dashboards are built to make that platform look good. Meta counts a conversion it may not have caused. Shopify counts revenue before returns. GA4 counts sessions and attributes them by its own model. Put three of them side by side and you get three answers to the same question.
So the dashboard exists, but the team quietly stops trusting it, and decisions drift back to whoever has the strongest opinion in the room.
Built on a reconciled warehouse instead, a dashboard becomes something people cite rather than argue with. That's the difference between reporting and decision-making.
Delivered, not described.
Executive overview
Revenue, blended ROAS, CAC, MER and contribution margin in one view, with period comparisons that make sense.
True contribution margin per SKU
Orders joined to ad spend and cost of goods, so you can see which products actually earn — usually the biggest surprise in the build.
Channel and campaign drill-down
Blended figures at the top, with the ability to go down to campaign level without leaving the page.
Scheduled delivery
Email and Slack on the cadence you pick. The people who need the number don't have to go looking for it.
Documented formulas
Every figure's calculation written on the page, so nobody has to ask what it means six months later.
What actually happens.
Scope
We agree the ten or so questions the dashboard has to answer. Everything else is noise.
Model
The metrics get defined once in the warehouse so every view reads the same numbers.
Build
Looker Studio, in your account, with your branding — or your client's if you're an agency.
Deliver
Scheduled refresh, email and Slack set up, and a walkthrough with whoever uses it.
Faisal understands our clients' needs and translates them into clear, insightful dashboards that elevate how we present data.
VERIFIED CLIENT REVIEW · AGENCY ENGAGEMENT, 132 HOURS · AUG 2025
Asked on nearly every call.
Do we need the warehouse first?
For anything blending more than two sources, yes. A dashboard built directly on platform connectors will reproduce exactly the disagreement you're trying to fix. For a single-source view, we can go straight to the dashboard.
Looker Studio or something else?
Looker Studio for most cases — it's free, it sits next to BigQuery, and your team can be taught to edit it. If you're already standardised on Power BI or Tableau, I'll build there instead.
Can we edit it ourselves afterwards?
Yes. It's in your account with full edit rights, and the handover covers how it's put together.
Want this on your own numbers?
Fifteen minutes, no pitch. Bring the figure you least trust and I'll tell you what's likely behind it.
Book a 15-minute call